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| Main Author: | |
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| Format: | Preprint |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2101.05841 |
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| _version_ | 1866913510558007296 |
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| author | Wegner, Sven-Ake |
| author_facet | Wegner, Sven-Ake |
| contents | These are lecture notes based on the first part of a course on 'Mathematical Data Science', which I taught to final year BSc students in the UK in 2019-2020. Topics include: concentration of measure in high dimensions; Gaussian random vectors in high dimensions; random projections; separation/disentangling of Gaussian data. A revised version has been published as part of the textbook [Mathematical Introduction to Data Science, Springer, Berlin, Heidelberg, 2024, https://link.springer.com/book/10.1007/978-3-662-69426-8]. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2101_05841 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | Lecture notes on high-dimensional data Wegner, Sven-Ake Functional Analysis Machine Learning 68P01 These are lecture notes based on the first part of a course on 'Mathematical Data Science', which I taught to final year BSc students in the UK in 2019-2020. Topics include: concentration of measure in high dimensions; Gaussian random vectors in high dimensions; random projections; separation/disentangling of Gaussian data. A revised version has been published as part of the textbook [Mathematical Introduction to Data Science, Springer, Berlin, Heidelberg, 2024, https://link.springer.com/book/10.1007/978-3-662-69426-8]. |
| title | Lecture notes on high-dimensional data |
| topic | Functional Analysis Machine Learning 68P01 |
| url | https://arxiv.org/abs/2101.05841 |